# -*- coding: utf-8 -*-
#
# conncon_targets.py
#
# This file is part of NEST.
#
# Copyright (C) 2004 The NEST Initiative
#
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# NEST is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with NEST.  If not, see <http://www.gnu.org/licenses/>.

"""
Spatial networks: Convergent projection and rectangular mask, from source perspective
-------------------------------------------------------------------------------------

Create two populations of iaf_psc_alpha neurons on a 30x30 grid
Connect the two populations with convergent projection and rectangular mask, and
visualize connections from source perspective

BCCN Tutorial @ CNS*09
Hans Ekkehard Plesser, UMB
"""

import matplotlib.pyplot as plt
import nest
import numpy as np

nest.ResetKernel()

pos = nest.spatial.grid(shape=[30, 30], extent=[3.0, 3.0], edge_wrap=True)

########################################################################
# create and connect two populations
a = nest.Create("iaf_psc_alpha", positions=pos)
b = nest.Create("iaf_psc_alpha", positions=pos)

cdict = {
    "rule": "pairwise_bernoulli",
    "p": 0.5,
    "use_on_source": True,
    "mask": {"rectangular": {"lower_left": [-0.2, -0.5], "upper_right": [0.2, 0.5]}},
}

nest.Connect(a, b, conn_spec=cdict, syn_spec={"weight": nest.random.uniform(0.5, 2.0)})

#####################################################################
# first, clear existing figure, get current figure
plt.clf()
fig = plt.gcf()

# plot targets of two source neurons into same figure, with mask
for src_index in [30 * 15 + 15, 0]:
    # obtain node id for center
    src = a[src_index : src_index + 1]
    nest.PlotTargets(src, b, mask=cdict["mask"], fig=fig)

# beautify
plt.axes().set_xticks(np.arange(-1.5, 1.55, 0.5))
plt.axes().set_yticks(np.arange(-1.5, 1.55, 0.5))
plt.grid(True)
plt.axis([-2.0, 2.0, -2.0, 2.0])
plt.axes().set_aspect("equal", "box")
plt.title("Connection targets")

plt.show()

# plt.savefig('conncon_targets.pdf')
